What is the main idea behind SVD (Single Value Decomposition)?
How do you solve a LLS problem using SVD?
What is the cost of the SVD method? When is it best to use this method?
How can SVD and the eucl norm of a matrix a be used?
How can the SVD be used for the pseudoinverse?
How can the SVD be used for the condition number?
ERROR propagation, does not make sense without own notes
How to the three different methods compare? How sensitive is each method?
What is a projection?
What is QR decomposition with column pivoting?